Big Data

How Big Data Is Impacting the Oil Industry

The similarities between big oil and big data are remarkable. They’re both incredibly valuable as long as they keep “flowing” and we have access to them and a solid plan for putting them to work.

Interestingly, the two industries complement each other in many ways. With the arrival of big data and related technologies into the mainstream, the oil industry is probably never going to look back. Here’s why.

Why Bring Big Data to the Oil Industry?

The thing about big data is that it’s merely putting to work the information we already gather and, in many cases, already store. But like oil sitting in the ground, nobody can profit if that’s where it remains. The most relevant data must first get identified, then sorted and stored in such a way that all pertinent parties or applicable programs can retrieve and gather useful insights from it. All of this is in service of making the industry more efficient overall — and even more profitable.

Part of the problem, though, is that the oil industry is both risk-averse and risk-prone. Oil prices throughout the world fluctuate regularly and sometimes rapidly, and with more public alarm over new drilling and fracking sites than ever, it stands to reason heavy lifters in the industry want access to tools that can help them thread the needle between profitability, public oversight and general trends in the industry.

Plus, the promise and the threat of globalization means every company in the oil industry has to work even harder and smarter to compete. That means finding opportunities to make improvements and working to cut back on waste — which is where big data excels.

Opportunity Areas and Tips for Bringing Big Data to Your Oil Company

Shale is a sedimentary rock found throughout the world. Among its several stratified layers is the organic material which can be refined into both oil and natural gas. But finding and making the most of drilling and fracking sites is a challenge. According to the Manhattan Institute, this is one of the most significant challenges and opportunities in the modern oil industry:

“Bringing analytics to the complexities of shale geology, geophysics, stimulation and operations to optimize the production process would potentially double the number of effective stages, thereby doubling output per well and cutting the cost of oil in half.”

In half? If that’s not a call to action, we don’t know what is. But how can we achieve that goal?

1. Apply Analytics to Geographical Surveys

Geography is a hugely important factor when it comes to prospecting for oil. And while the layers of rock and their composition and thicknesses can vary between regions, analytics can help you apply the lessons you’ve already learned from your operations in one region to others you might be considering.

GIS, or geographical information systems, are your likeliest allies in finding suitable sites based on known regional characteristics, as well as your previous failures and successes. With mapping and analytical technology like this, each of your experiences becomes a data-driven learning experience.

2. Use Conditional Monitoring to Maximize Uptime and Machine Life

Oil drilling equipment is some of the hardest-working machinery you’ll find anywhere. The relentless demand for oil across the world means companies need to work long hours under grueling conditions and variable temperatures.

Big data is an ally here, too. It comes in the form of sensors either built into equipment or added afterward in a retrofit. These sensors can take in information from the environment and the machine itself to remotely tell operators whether the situation is within tolerances or whether the equipment is struggling — or even about to fail.

We don’t need to remind you oil companies are not fans of downtime. Using more intelligent machinery helps ensure engineers can respond to drill bit or engine issues in near-real time and before a part or entire machine fails and brings the whole operation to a standstill.

Some estimates indicate the average oil company could reduce its expenses by 10 to 50 percent by gathering data from, and applying condition-based monitoring to, the equipment they use onsite.

3. Hire the Right Data Talent

Almost every industry under the sun is contributing to the ongoing high demand for data analysts. By 2020, says IBM, demand for graduates and professionals in this field will grow by another 28 percent.

What kind of expectations should you have for your data analysts, though? Among other things, your technicians should be well-versed in existing and upcoming technologies. They should know how to make a thorough cost-benefit analysis when it comes to making a hardware or software upgrade.

Unnecessary tech upgrades, or purchases made without a compelling use case, can cost companies a lot of money and threaten their very financial solvency. But the right update at the right time could be a windfall. When you’re expanding your operations, and you want data science and gifted analysts on your side, look for individuals who have solid analytical credentials and good instincts about where technology is heading.

For instance, some are predicting blockchain-based technologies could cut expenses by 15 to 25 percent for an individual company — and by as much as $5 to $10 billion throughout the entire reinsurance industry. The concept applies to big oil just as readily: Blockchain offers perhaps the most exceptional level of industrial oversight currently available, thanks to its ability to create a truly transparent and immutable public record of every action a company and its partners undertake.

We’ve been talking mostly about front-line technology applied to oil fields and rigs out at sea. But blockchain technology is becoming more of an ally for the back office, where transparency and accountability for every drop of oil aren’t remotely optional anymore.

Growing Pains and Opportunities

It’s easy to understand having reservations about bringing new types of technology or talent aboard. And as we’ve been discussing, it’s not always easy to tell when a piece of technology will live up to its promise or prove a worthy addition to your workflows.

There’s never been a better time to explore this potential. Only a very few companies worldwide — 4 percent, by some estimates — are in a position right now to realize meaningful results from data analysis. Now could be your moment to seize a very real competitive advantage through the right technologies, the right data partners and the right hiring decisions.


Image Credit: Erik Christensen

Photo License & Source: CC BY-SA 3.0 via Wikimedia Commons

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